Abstract
<strong class="journal-contentHeaderColor">Abstract.</strong> Cosmic-ray neutron sensing (CRNS) allows for non-invasive soil moisture estimations at the field scale. The derivation of soil moisture generally relies on secondary cosmic-ray neutrons in the epithermal to fast energy ranges. Most approaches and processing techniques for observed neutron intensities are based on the assumption of homogeneous site conditions or of soil moisture patterns with correlation lengths shorter than the measurement footprint of the neutron detector. However, in view of the non-linear relationship between neutron intensities and soil moisture, it is questionable whether these assumptions are applicable. In this study, we investigated how a non-uniform soil moisture distribution within the footprint impacts the CRNS soil moisture estimation and how the combined use of epithermal and thermal neutrons can be advantageous in this case. Thermal neutrons have lower energies and a substantially smaller measurement footprint around the sensor than epithermal neutrons. Analyses using the URANOS (Ultra RApid Neutron-Only Simulation) Monte Carlo simulations to investigate the measurement footprint dynamics at a study site in northeastern Germany revealed that the thermal footprint mainly covers mineral soils in the near-field to the sensor while the epithermal footprint also covers large areas with organic soils. We found that either combining the observed thermal and epithermal neutron intensities by a rescaling method developed in this study or adjusting all parameters of the transfer function leads to an improved calibration against the reference soil moisture measurements in the near-field compared to the standard approach and using epithermal neutrons alone. We also found that the relationship between thermal and epithermal neutrons provided an indicator for footprint heterogeneity. We, therefore, suggest that the combined use of thermal and epithermal neutrons offers the potential of a spatial disaggregation of the measurement footprint in terms of near- and far-field soil moisture dynamics.
Highlights
Soil moisture is a key variable in the hydrological cycle (e.g., Vereecken et al, 2008, 2014; Seneviratne et al, 2010) driving i.e. energy fluxes, groundwater recharge, runoff generation processes and biomass production which in turn, influence climatic variables on varying spatio-temporal scales
We found that either combining the observed thermal and epithermal neutron intensities by a rescaling method developed in this study, or adjusting all parameters of the transfer function leads to an improved calibration against reference soil moisture measurements in the near field compared to the standard approach and using epithermal neutrons alone
We found that the 15 relationship between thermal and epithermal neutrons provided an indicator for footprint heterogeneity
Summary
Soil moisture is a key variable in the hydrological cycle (e.g., Vereecken et al, 2008, 2014; Seneviratne et al, 2010) driving i.e. energy fluxes, groundwater recharge, runoff generation processes and biomass production which in turn, influence climatic variables on varying spatio-temporal scales (e.g. see, Daly and Porporato, 2005; Vereecken et al, 2008; Seneviratne et al, 2010; Wang et al, 2018). Observations of soil moisture have a high importance for the estimation of landscape water balances and hydrological modelling These applications would profit especially from field-scale observations covering several hectares. Introduced about a decade ago, Cosmic-Ray Neutron Sensing (CRNS) (e.g., Zreda et al, 2008; Desilets et al, 2010) partly overcomes these issues and allows for non-invasive soil moisture estimation at the field scale It provides a representative spatially averaged soil moisture value across the instrument’s measurement footprint (Schrön et al, 2018b) of approximately 12 hectares. As a result uncertainties may arise when hydrogen is not distributed homogeneously in the footprints as mentioned by Bogena et al (2020) and this limits 65 the applicability of combining thermal and epithermal neutrons This may be of particular importance as most studies with stationary CRNS assume homogeneous site conditions. Previous studies confirmed the applicability of CRNS at heterogeneous study sites for deriving spatially averaged soil moisture time series (e.g., Franz et al, 2016; Sigouin et al, 2016; Schrön et al, 2017; Pang et al, 2021), approaches for the spatial disaggregation of CRNS-derived soil moisture values at heterogeneous observation sites have not been assessed in detail yet
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